Theme 3: Financial Conditions

This collection of Jupyter notebooks introduces quantamental indicators of macro-financial conditions.

Financial conditions here refer to daily information states of economic and market factors that influence the ease of borrowing and raising capital in an economy. These typically are combinations of economic and market data and include metrics of real interest rates, real effective currency appreciation, terms-of-trade, credit growth, as well as central bank liquidity generation.

Financial conditions are often among the most timely indicators of changes in economic development. For example, real interest rates, real exchange rates, and terms of trade can be tracked almost in real-time and large shifts can be game changers for board economic dynamics. Moreover, financial conditions can also indicate risks of disruptions in financial markets. For example, an economy with a recent history of fast credit growth and a sudden surge in real interest rates may be at risk of a forthcoming credit crunch.

Indicators are organized in categories, i.e. panels of one type of indicator over as many currency areas or markets as are available. Then the categories are grouped by similarity and each group is presented in a notebook.

The notebooks define and document the categories, describe their panels of time series, and provide some examples to illustrate their relevance for trading and algorithmic strategies. Most importantly, the notebooks are downloadable and can be used as a basis for exploring the respective categories interactively and relating them to generic financial returns with a few lines of Python code. All notebooks use the Macrosynergy Python package of standard functions for downloading, plotting, and analyzing data in standard JPMaQS format.